In the Developmental Intelligence Laboratory, we are interested in understanding fundamental cognitive mechanisms of human intelligence, human learning, and human interaction and communication in everyday activities. To do so, we collect and analyze micro-level multimodal behavioral data using state-of-the-art sensing and computational techniques. One of our primary research aims is to understand human learning and early development. How do young children acquire fundamental knowledge of the world? How do they select and process the information around them and learn from scratch? How do they learn to move their bodies and to communicate and interact with others? Learning this kind of knowledge and skills is the core of human intelligence. To understand how human learners achieve the learning goal, the primary approach in our research is to attach GoPro-like cameras on the head of young children to record egocentric video from their point of view. Using this innovative approach, we've been collecting video data of children’s everyday activities, such as playing with their parents and their peers, reading books with parents and caregivers, and playing outside. We've been using state-of-the-art machine learning and data mining approaches to analyze high-density behavioral data. This research line will ultimately solve the mystery on why human children are such efficient learners. Moreover, the findings from our research will be used to help improve learning of children with developmental deficits. A complimentary research line is to explore how human learning can teach us about how machines can learn. Can we model and simulate how a human child learns and develops? To this end, our research aims at bridging and connecting developmental science in psychology and machine learning and computer vision in computer science.
(Visit: http://www.uctv.tv/) Robert Bjork, Distinguished Research Professor in the UCLA Department of Psychology, shares insights from his work as a renowned...
IBM is transforming the learning experience with cognitive solutions that help educators gain insights into learning styles, preferences, and aptitude of every student.
Sana utilizes artificial intelligence to closely personalize content to the needs of each student. We offer real-time content recommendations for forward-thinking education companies around the world.
This research study reports 5 powerful e-learning strategies that can accelerate time to proficiency in complex cognitive skills: Experience-rich multi-technology mix, Time-spaced micro-learning content, Scenario-based contextualization, On-demand performance support systems, and Optimally sequenced e-learning path.
This volume provides a thorough and up-to-date synthesis of the expansive and highly influential literature on the cognitive neuroscience of addiction from the last 30 years. Bringing together contributions from leading authorities in the field, it places emphasis on the most commonly investigated drugs of abuse.
Computer science as a field requires curricular guidance, as new innovations are filtered into teaching its knowledge areas at a rapid pace. Furthermore, another trend is the growing number of students with different cultural backgrounds. These developments require taking into account both the differences in learning styles and teaching methods in practice in the development of curricular knowledge areas. In this paper, an intensive collaborative teaching concept, Code Camp, is utilized to illustrate the effect of learning styles on the success of a course. Code Camp teaching concept promotes collaborative learning and multiple skills and knowledge in a single course context. The results indicate that Code Camp as a concept is well liked, increases motivation to learn and is suitable for both intuitive and reflective learners. Furthermore, it appears to provide interesting creative challenges and pushes students to collaborate and work as a team. In particular, the concept also promotes intuition.
J. Gutzeit, L. Weller, J. Kürten, und L. Huestegge. Journal of Experimental Psychology: Human Perception and Performance, 49 (6):
759--773(2023)Place: US
Publisher: American Psychological Association.